1. Field of the Invention
The invention relates generally to the field of medical imaging. More particularly, the invention relates to the analysis of color medical images to detect abnormalities in the subject tissue.
2. Discussion of the Related Art
Despite the dramatic progress of multimedia information technology and its rapid spread into the medical profession, discussions on medical images so far have concentrated largely on sufficient spatial sampling rate and sufficient grayscale gradations for black and white pictures such as X-ray, CT and MRI. The problems concerning the transmission of medical color images such as endoscopic and dermatological images have not, however, been discussed intensively.
Color image analysis has been extensively used in dermatology and in the assessment of wound healing (Herbin et al., Haeghen et al.). Nischik et al. in 1997 developed a method to analyze the spreading of skin erythemas by determining the change in the color of the skin from true color images in the CIE L*a*b* color space. Also, Herbin et al. in 1990 determined a quantitative analysis for the follow up of skin lesions. Considering that each imaging system has its own time-varying RGB color space that depends on its own unique spectral sensitivities, it remains difficult to accurately describe colors in device-dependent RGB. Therefore, it has been found that the use of a device-dependent red-green-blue (RGB) color spaces is a problem.
A color calibration method for correcting for the variations in RGB color values caused by the imaging system components was developed and tested by Chang et al. in 1996. They tried to reduce the variations caused by additive and multiplicative errors in the RGB color values. Herbin et al. tried to determine the best color space for use in the field of dermatology. Haeghen et al. extensively discussed a method to convert the device-dependent RGB color space into a device-independent color space called sRGB. Others have addressed the problem of finding a transform between the device-dependent color space to a device-independent color space (Herbin et al., Haeghen et al., Chang et al., Kang et al.).
Knyrim et al. have demonstrated that the Olympus video endoscopes reproduces hue very well but desaturates the color. A color calibration method may correct for this desaturation problem.
The International Commission on Illumination (CIE) is a standards body in the field of color science. They have defined additional color spaces, such as CIE XYZ and CIE L*a*b*, which describe color based on differences perceived in the human visual system (Giorgianni et al.). As described in Herbin et al., Haeghen et al., and Nischik et al., the CIE L*a*b* system has been found to be the best color space in which to make measurements. The device-independent color space sRGB has a known relationship with CIE XYZ and CIE L*a*b* color spaces (Giorgianni et al.). In the CIE L*a*b* space, colors can be compared by computing a distance metric ΔE that is proportional to the color deviation as seen by a human observer.
Other color spaces are also suitable for color comparisons; in the assessment of wound healing kinetics, the hue-saturation-value (HSV) color space was found to be a good representation for the color index (Herbin, Fox et al.). The sRGB device-independent color space also has a known relationship with HSV color space and the HSV space may be easier for humans to understand and interpret than CIE L*a*b* (Giorgianni et al.).